The present invention relates to a waveform evaluating apparatus for evaluating waveforms measured by a synchroscope or such a measuring apparatus and more particularly to a waveform evaluating apparatus using a neural network in which a plurality of neural network modules are independently provided for each of objects of judgment and neural weight ratios thereof are determined by causing them to learn with a first ideal waveform module being an ideal signal and a second ideal waveform module corresponding to an element as the object of judgment.
Further, the present invention relates to a waveform evaluating apparatus capable of quantitatively evaluating a change in waveform made during an environmental test, by performing a waveform adjustment using a neural network. Furthermore, the present invention relates to a waveform evaluating apparatus most suited for use in inspecting apparatuses for inspecting good or bad quality and the like for example of printed circuit boards.
In the past, for evaluating a waveform measured by a synchroscope or the like, there were only such ways as to use programs or the like prepared in conformity with the shape of the waveform or that in which an observer evaluates the waveform by visual examination. Further, to adjust the waveform, there was only a way in which an observer adjusts the waveform while visually checking it.
In the evaluation of waveforms by means of programs or the like, since the waveform assumes a variety of shapes, there was such a problem that the evaluating programs had to be prepared for each of the waveforms and this was quite troublesome. Further, it was a problem that such a program was not usable for general purposes and poor in efficiency. Furthermore, in the case of evaluation of analog waveforms, there was a problem that it was difficult to describe the evaluation in programs, while, in the evaluation of them by visual examination, it was a problem that personal error was produced from observer to observer and, hence, a quantitative evaluation was impossible.
Besides, an electric signal waveform obtained from an object of judgment is composed of a variety of elements, and in such elements there are those serving as the objects of waveform evaluation and also those unnecessary for the evaluation.
In the case of an analog waveform including a large quantity of noise components such as random noises N1, high-frequency noises N2, and the like as shown in FIG. 25, adjustment and evaluation of the waveform was difficult and considerable personal errors were produced depending on observers, and it was difficult to achieve a quantitative evaluation.
Accordingly, there have been great demands for a waveform evaluating apparatus not requiring description of programs, capable of evaluating any types of waveform even if they include great quantities of noises, free of personal error, and capable of numerically expressing the quantities for adjustments.